Move data to and from Azure Blob storage

The Team Data Science Process requires that data be ingested or loaded into a variety of different storage environments to be processed or analyzed in the most appropriate way in each stage of the process.

Different technologies for moving data

The following articles describe how to move data to and from Azure Blob storage using different technologies.

Which method is best for you depends on your scenario. The Scenarios for advanced analytics in Azure Machine Learning article helps you determine the resources you need for a variety of data science workflows used in the advanced analytics process.

Note

For a complete introduction to Azure blob storage, refer to Azure Blob Basics and to Azure Blob Service.

Using Azure Data Factory

As an alternative, you can use Azure Data Factory to:

  • create and schedule a pipeline that downloads data from Azure blob storage,
  • pass it to a published Azure Machine Learning web service,
  • receive the predictive analytics results, and
  • upload the results to storage.

For more information, see Create predictive pipelines using Azure Data Factory and Azure Machine Learning.

Prerequisites

This article assumes that you have an Azure subscription, a storage account, and the corresponding storage key for that account. Before uploading/downloading data, you must know your Azure Storage account name and account key.